A self-scanned image sensor employing MOS structure

1970 ◽  
Vol 58 (2) ◽  
pp. 247-248 ◽  
Author(s):  
T. Ando ◽  
Y. Ishihara ◽  
T. Akahoshi
Keyword(s):  
Image Sensor ◽  
Mos Structure ◽  
Scanned Image

scholarly journals Measuring the spatial distribution of multiply scattered light using a de-scanned image sensor for examining retinal structure contrast

2021 ◽  
Vol 29 (2) ◽  
pp. 552
Author(s):  
Benjamin S. Sajdak ◽  
Jack T. Postlewaite ◽  
Kevin W. Eliceiri ◽  
Jeremy D. Rogers
Keyword(s):  
Spatial Distribution ◽  
Scattered Light ◽  
Image Sensor ◽  
Scanned Image ◽  
Retinal Structure

Development of Wafer Level Chip Size Packaging Process and its Application to the CMOS Image Sensor Module for Medical Device

2017 ◽  
Vol 137 (2) ◽  
pp. 48-58
Author(s):  
Noriyuki Fujimori ◽  
Takatoshi Igarashi ◽  
Takahiro Shimohata ◽  
Takuro Suyama ◽  
Kazuhiro Yoshida ◽  
...  
Keyword(s):  
Medical Device ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Wafer Level ◽  
Packaging Process ◽  
Sensor Module ◽  
Chip Size

Current and Future 3D-LSI Technology for the Image Sensor Devices

2008 ◽  
Author(s):  
Makoto Motoyoshi ◽  
Hirofumi Nakamura ◽  
Manabu Bonkohara ◽  
Mitsumasa Koyanagi
Keyword(s):  
Image Sensor ◽  
Sensor Devices

An Over 120dB Dynamic Range Linear Response Single Exposure CMOS Image Sensor with Two-stage Lateral Overflow Integration Trench Capacitors

2020 ◽  
Vol 2020 (7) ◽  
pp. 143-1-143-6 ◽  
Author(s):  
Yasuyuki Fujihara ◽  
Maasa Murata ◽  
Shota Nakayama ◽  
Rihito Kuroda ◽  
Shigetoshi Sugawa
Keyword(s):  
Linear Response ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Signal To Noise ◽  
Single Exposure ◽  
Two Stage ◽  
Noise Ratio ◽  
Maximum Signal

This paper presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration trench capacitors (LOFITreCs) exhibiting over 120dB dynamic range with 11.4Me- full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70dB. The measured SNR at all switching points were over 35dB thanks to the proposed two-stage LOFITreCs.

A practical approach on non-regular sampling and universal demosaicing of raw image sensor data

2020 ◽  
Vol 2020 (1) ◽  
pp. 91-95
Author(s):  
Philipp Backes ◽  
Jan Fröhlich
Keyword(s):  
Image Quality ◽  
Source Code ◽  
Image Sensor ◽  
Sensor Data ◽  
Color Filter ◽  
Lowpass Filter ◽  
Sampling Errors ◽  
Regular Sampling ◽  
Single Sensor ◽  
Similar Image Quality

Non-regular sampling is a well-known method to avoid aliasing in digital images. However, the vast majority of single sensor cameras use regular organized color filter arrays (CFAs), that require an optical-lowpass filter (OLPF) and sophisticated demosaicing algorithms to suppress sampling errors. In this paper a variety of non-regular sampling patterns are evaluated, and a new universal demosaicing algorithm based on the frequency selective reconstruction is presented. By simulating such sensors it is shown that images acquired with non-regular CFAs and no OLPF can lead to a similar image quality compared to their filtered and regular sampled counterparts. The MATLAB source code and results are available at: http://github. com/PhilippBackes/dFSR

A Study of Different Methodologies Helpful in the Identification of Offline Handwritten Script

2018 ◽  
Vol 6 (6) ◽  
pp. 307
Author(s):  
Manish M. Kayasth ◽  
Bharat C. Patel
Keyword(s):  
Feature Extraction ◽  
Character Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Post Processing ◽  
Classification Technique ◽  
Scanned Image ◽  
Gujarati Language ◽  
High Degree ◽  
Selection Of

The entire character recognition system is logically characterized into different sections like Scanning, Pre-processing, Classification, Processing, and Post-processing. In the targeted system, the scanned image is first passed through pre-processing modules then feature extraction, classification in order to achieve a high recognition rate. This paper describes mainly on Feature extraction and Classification technique. These are the methodologies which play an important role to identify offline handwritten characters specifically in Gujarati language. Feature extraction provides methods with the help of which characters can identify uniquely and with high degree of accuracy. Feature extraction helps to find the shape contained in the pattern. Several techniques are available for feature extraction and classification, however the selection of an appropriate technique based on its input decides the degree of accuracy of recognition. 

Development of a Pixel of Area Image Sensor in X-ray Detector

2018 ◽  
Vol 23 (6) ◽  
pp. 573-585
Author(s):  
D.A. Suponnikov ◽  
◽  
A.N. Putilin ◽  
E.A. Tatarinova ◽  
Z.G. Zhgunev ◽  
...  
Keyword(s):  
Image Sensor ◽  
X Ray

Extending Electrical Scanning Probe Microscopy Measurements of Semiconductor Devices Using Microwave Impedance Microscopy

2015 ◽  
Author(s):  
Benedict Drevniok ◽  
St. John Dixon-Warren ◽  
Oskar Amster ◽  
Stuart L Friedman ◽  
Yongliang Yang
Keyword(s):  
Scanning Probe Microscopy ◽  
Semiconductor Devices ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Scanning Probe ◽  
Cross Sectional ◽  
Probe Microscopy ◽  
Dopant Profiling ◽  
Capacitance Voltage

Abstract Scanning microwave impedance microscopy was used to analyze a CMOS image sensor sample to reveal details of the dopant profiling in planar and cross-sectional samples. Sitespecific capacitance-voltage spectroscopy was performed on different regions of the samples.

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